The Smoothness Priors Concept

Kitagawa, Genshiro; Gersch, Will

doi:10.1007/978-1-4612-0761-0_3

Cited by 39 publications

(54 citation statements)

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“…To find fingerprints of this variability in the global temperature anomaly data is not a trivial task due to comparatively (to the 11-year cycle) short period of observations and due to the statistically non-stationary character of these data (with considerable time trends). To extract these fingerprints we will use a time series decomposition method developed in [33], [34], [35]. A time series is decomposed into a trend (like that shown in Fig.…”

Section: Impact Of the Solar Dynamics On Earth Climatementioning

confidence: 99%

“…[33], [34], [35]. In this method a nonstationary mean time series is decomposed into trend, autoregressive and noise components.…”

Section: Appendix Amentioning

confidence: 99%

“…where ε t is Gaussian white noise with zero mean [33], [34], [35]. Again, state space modeling and Kalman filter, are used for estimation of the model parameters by the maximum likelihood method.…”

Section: Appendix Amentioning

confidence: 99%

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Transitional solar dynamics and global warming

Bershadskii¹

2009

Physica A: Statistical Mechanics and its Applications

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Solar activity is studied using a cluster analysis of the time-fluctuations of the sunspot number. It is shown that in an Historic period the high activity components of the solar cycles exhibit strong clustering, whereas in a Modern period (last seven solar cycles: 1933-2007) they exhibit a white-noise (non-)clustering behavior. Using this observation it is shown that in the Historic period, emergence of the sunspots in the solar photosphere was strongly dominated by turbulent photospheric convection. In the Modern period, this domination was broken by a new more active dynamics of the inner layers of the convection zone. Then, it is shown that the dramatic change of the sun dynamics at the transitional period (between the Historic and Modern periods, solar cycle 1933-1944yy) had a clear detectable impact on Earth climate. A scenario of a chain of transitions in the solar convective zone is suggested in order to explain the observations, and a forecast for the global warming is suggested on the basis of this scenario. A relation between the recent transitions and solar long-period chaotic dynamics has been found. Contribution of the galactic turbulence (due to galactic cosmic rays) has been discussed. These results are also considered in a content of chaotic climate dynamics at millennial timescales.

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Section: Impact Of the Solar Dynamics On Earth Climatementioning

confidence: 99%

“…[33], [34], [35]. In this method a nonstationary mean time series is decomposed into trend, autoregressive and noise components.…”

Section: Appendix Amentioning

confidence: 99%

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Transitional solar dynamics and global warming

Bershadskii¹

2009

Physica A: Statistical Mechanics and its Applications

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“…Although more parameters can make the model more descriptive, the minimum AIC method itself can reimburse the deviation brought by the parameters before it gives out the final results. That means that AIC can show the consistency between reality and prediction and can test both the descriptive ability and predictive ability in a model comprehensively 13) . Overall, the model with the smallest AIC value can be regarded as the best one 2) .…”

Section: Model Evaluation By Aicmentioning

confidence: 99%

“…Here the AIC value was computed by adding twice the sum of all data to the AIC value of the model for the log-transformed data, so it is comparable with the others 13) .…”

Section: Aic Values Of the Three Models From The Data Of Experimentsmentioning

confidence: 99%

SH-Model: A Model Based on Both System and Human Effects for Pointing Task Evaluation

Ren

Kong

Jiang

2005

ipsjdc

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As a well-known human performance model, Fitts' law, a tool for evaluating pointing devices, has been accepted and applied for a long time in the human computer interaction field. However, doubts now exist regarding its validity. One challenging job for those who are doing research on human performance models is to resolve the problem relating to input hits' distribution (i.e., spatial constraint). We developed a new model based on temporal distribution to alter the traditional models. The new model and the traditional models are compared in two experiments using AIC (Akaike's Information Criterion), a criterion for statistical model selection. The results show that the new model is better than the traditional ones in performance evaluation.

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Probabilistic reinforcement learning in adults with autism spectrum disorders

et al. 2011

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Background Autism spectrum disorders (ASDs) can be conceptualized as disorders of learning, however there have been few experimental studies taking this perspective. Methods We examined the probabilistic reinforcement learning performance of 28 adults with ASDs and 30 typically developing adults on a task requiring learning relationships between three stimulus pairs consisting of Japanese characters with feedback that was valid with different probabilities (80%, 70%, and 60%). Both univariate and Bayesian state–space data analytic methods were employed. Hypotheses were based on the extant literature as well as on neurobiological and computational models of reinforcement learning. Results Both groups learned the task after training. However, there were group differences in early learning in the first task block where individuals with ASDs acquired the most frequently accurately reinforced stimulus pair (80%) comparably to typically developing individuals; exhibited poorer acquisition of the less frequently reinforced 70% pair as assessed by state–space learning curves; and outperformed typically developing individuals on the near chance (60%) pair. Individuals with ASDs also demonstrated deficits in using positive feedback to exploit rewarded choices. Conclusions Results support the contention that individuals with ASDs are slower learners. Based on neurobiology and on the results of computational modeling, one interpretation of this pattern of findings is that impairments are related to deficits in flexible updating of reinforcement history as mediated by the orbito-frontal cortex, with spared functioning of the basal ganglia. This hypothesis about the pathophysiology of learning in ASDs can be tested using functional magnetic resonance imaging.

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The Smoothness Priors Concept

Cited by 39 publications

References 0 publications

Transitional solar dynamics and global warming

Transitional solar dynamics and global warming

SH-Model: A Model Based on Both System and Human Effects for Pointing Task Evaluation

Probabilistic reinforcement learning in adults with autism spectrum disorders

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